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Cited by 11,064Lung Cancer Diagnosis and TreatmentGlobal Cancer Incidence and ScreeningOccupational and environmental lung diseases

Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening

Open access
The National Lung Screening Trial Research Team·2011·New England Journal of Medicine
DOI 10.1056/nejmoa1102873PMC PMC4356534
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Abstract

BACKGROUND: The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer. METHODS: From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. RESULTS: The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02). CONCLUSIONS: Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385.).

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Crossref · 10.1056/nejmoa1102873

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  • Low-dose CT was shown to be useful for lung cancer screening.

    “For example, low-dose CT was shown to be useful for lung cancer screening [51].”

    From Convolutional neural networks: an overview and application in radiology (2018) · cites this paper as [51]

  • Risk prediction was robust across multiple clinical scenarios, including a primary prevention asymptomatic setting with non-gated chest CT, and dedicated ECG-gated cardiac CT in stable and acute chest pain settings.

    “Risk prediction was robust across multiple clinical scenarios, including a primary prevention asymptomatic setting with non-gated chest CT (NLST)18, as well as dedicated ECG-gated cardiac CT in stable (PROMISE)19 and acute (ROMICAT-II)20 chest pain setting.”

    From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [18]

  • The majority of FHS (100%), NLST (91%), PROMISE (77%), and ROMICAT-II (66%) participants were non-Hispanic whites.

    “The majority of FHS (100%)44, NLST (91%)18, PROMISE (77%)45, and ROMICAT-II (66%)46 participants were non-Hispanic whites.”

    From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [18]

    The Results section, “Characteristics of the Participants” (page unavailable), refers to demographic characteristics in Table 1, but the passages in our copy do not give the proportion of NLST participants who were non-Hispanic white. Searches for race, ethnicity, and 91% did not locate that figure. The other trials have separate citations and are not attributed to this source. (LLM, conf=0.70)

    Experimental — accuracy not yet measured

  • In NLST, the coronary calcium score was measured manually in 396 randomly selected participants using 3D Slicer (V4).

    “In NLST18, the coronary calcium score was measured manually in 396 randomly selected participants using 3D Slicer (V4).”

    From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [18]

    The Methods > Screening passages describe NLST lung-cancer screening and CT image interpretation, but do not address coronary calcium scoring. Searches for “396,” “coronary calcium score,” and “3D Slicer (V4)” found no passage documenting the claimed participant selection, manual measurement, or software. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • The National Lung Cancer Screening Trial has become a key public data resource for machine learning research.

    “including the National Lung Cancer Screening Trial (NLST), which has become a key public data resource for machine learning research.”

    From Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions (2024) · cites this paper as [27]

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1 of the 29 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

  1. [6]Cigarette smoking among adults and trends in smoking cessation — United States, 2008 MMWR Morb Mortal Wkly Rep 2009 58 1227 32 19910909
  2. [17]Izmirlian G Estimation of the relative risk following group sequential procedure based upon the weighted log-rank statistic arXiv Cornell University Library 2011 http://arxiv.org/abs/1102.5088 · arXiv
  3. [27]NCI NLST press conference NCI radio broadcasts 11 2010 http://www.cancer.gov/newscenter/radio-broadcasts

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Authors
The National Lung Screening Trial Research Team
Affiliations
National Cancer Institute (US)
Corresponding author
The National Lung Screening Trial Research Team
Venue
New England Journal of Medicine
Publisher
Massachusetts Medical Society
Published
2011-08-04
Volume
365
Issue
5
Pages
395-409
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
DOI
10.1056/nejmoa1102873
PMC
PMC4356534
OpenAlex
W130099911
Cited by
11,064
References
29
Citations by year
2026: 748 · 2025: 875 · 2024: 940 · 2023: 943 · 2022: 930 · 2021: 955 · 2020: 887 · 2019: 757 · 2018: 723 · 2017: 591 · 2016: 591 · 2015: 610 · 2014: 527 · 2013: 494 · 2012: 374
FWCI
406.72
Type
journal article
Language
en
Open access
Locations
  • New England Journal of Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (n01cn025516-044, n01cn025515-047, n01cn025513-043, n02cn63300-11-0-5, 1ul1rr033176-01, n01cn025514-038, n01cn025511-041, n01cn025524-036, n01cn075022-017, n01cn025476-008, n01cn025522-043, n01cn025512-050, UL1TR000124, n01cn025518-039, 3u10ca079778-14s1)
  • National Cancer Institute (U01CA079778, N01 CN25514, N01 CN025511, N02-CN-63300, N01-CN-25 522, N01 CN-25524, N01-CN-25 476, N01 CN25515, U10CA080098, U01-CA-80098, N01 CN025516, U01 CA79778, N01 CN025515, N01 CN025514, U01CA080098, N01CN25511, N02 CN063300, N01 CN025522, U10 CA079778, N01 CN025476, N01CN75022, N01 CN025518, N01 CN025512, N01 CN025513, N01 CN075022, N01-CN-25513, N01 CN025524, N01 CN25512, N01CN25518, N01-CN-25 516)
  • National Center for Research Resources (UL1-RR-033176)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
  • Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Occupational and environmental lung diseases
Keywords
lung cancer screening, low-dose CT, lung cancer mortality, National Lung Screening Trial, chest radiography, screening adherence, false positives, lung cancer incidence, early cancer detection, high-risk individuals, cancer mortality reduction, lung cancer risk factors, smoking, chronic obstructive pulmonary disease, radon
MeSH terms
Aged, Female, Humans, Lung Neoplasms, Male, Middle Aged, Patient Compliance, Radiography, Thoracic, Tomography, X-Ray Computed, Bias, Incidence

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